Papers by Shuhan Qi
Merge then Realign: Simple and Effective Modality-Incremental Continual Learning for Multimodal LLMs (2025.emnlp-main)
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| Challenge: | Recent advances in Multimodal Large Language Models (MLLMs) have enhanced their versatility as they integrate a growing number of modalities. |
| Approach: | They propose a simple MCL paradigm that addresses forgetting and misalignment . they propose 'MErge then ReAlign' to extend existing models to more modalities . |
| Outcome: | The proposed paradigm is easy to deploy and highly reusable in the MLLM community. |
MDIT-Bench: Evaluating the Dual-Implicit Toxicity in Large Multimodal Models (2025.findings-acl)
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| Challenge: | Large Multimodal Models (LMMs) have raised concerns about model toxicity. |
| Approach: | They propose a model to measure the toxicity gap between models and their hard level to determine whether they can handle dual-implicit toxicity. |
| Outcome: | The proposed model can handle dual-implicit toxicity effectively on 13 prominent LMMs, but its performance drops significantly in hard level. |